Why stakeholders don’t care about your data engineering work (yet)
Because you’re solving the wrong problem and it’s costing you trust, visibility, and growth
This article is part of the Translating data work into business value playlist. Click here to explore the full series.
This article is part of the Business impact translation system playlist. Click here to explore the full series.
Hi fellow data pro, Yordan here,
I thought hard work was enough.
Back at my last job, I was leading the data infrastructure for one of the company’s biggest strategic bets.
It was a monster.
Late nights. Canceled meetings. Twelve-hour days buried in pipelines and infra. I was heads-down making the whole thing work. Driving ingestion, managing dependencies, and tuning infra.
I wasn’t just supporting the project. I was the spine of it.
I missed team lunches. I ghosted planning meetings. I figured everyone knew how mission-critical this work was.
But when the project wrapped up?
A peer of mine got promoted. Someone who had joined way after I did. Someone with half the experience.
They weren’t touching infra. They weren’t solving tech debt. They were writing daily updates.
Literally.
Morning Slack posts with timelines and KPIs. Evening updates with "no new updates."
They spoke the business language.
They were not mentioning the LookML models they were building.
They talked about what stakeholders cared about:
What got done
What was at risk
What this meant for the launch
And they got the credit.
You’re solving tech problems, not business ones
I wanted to be the quiet killer, someone who just delivered.
But here’s the truth:
Business doesn't reward invisible labor.
If your impact isn't tied to dollars, speed, or decisions, you're replaceable.
I was optimizing for elegance. They were optimizing for alignment.
I thought clean DAGs spoke for themselves. I thought faster pipelines would be obvious wins.
But nobody's ever said, "Q4 revenue missed target because the data model was slow."
They’ll say: "We didn’t know the churn spike until it was too late."
Different lens. Same problem.
Clean tech isn’t visible value
Let me say it again:
Hard work doesn't speak. Only humans do.
You can save 10 hours a week across the company and still be invisible. Because no one connects the dots from "refactored pipeline" to "more accurate board deck."
Unless you tell them.
I used to think updates were annoying. Redundant. "Why post if there's no progress?"
Turns out, presence builds perception.
And perception drives trust.
That peer of mine made their work feel like momentum.
Even if nothing moved, stakeholders knew the gears were turning.
And when the project wrapped? That trust paid off.
Business-first framing is the unlock
The difference wasn’t technical skill. It was translation.
I said: "We rebuilt the ingestion layer."
They said: "We’re on track to deliver reporting two days earlier than forecast."
I said: "Model joins are stable now."
They said: "There’s now no risk of missing customer KPIs in next week’s review."
Same outcomes. Different narratives.
Guess which one got airtime.
Stop building in a vacuum
This lesson hurt to learn:
Your work doesn’t matter unless people see its impact.
That promotion wasn’t stolen from me. I gave it away.
By staying quiet. By working in the dark. By assuming quality speaks louder than clarity.
Now, before I say yes to a build, I ask: "What business pain does this solve?"
If I can’t answer that in plain English, I pause.
Because code that doesn’t move a number is just code. And code alone doesn’t get you promoted.
Next week, I’ll show you exactly how I map every data project to a business pain, even when leadership has no idea what they want.
Thanks for reading,
PS: Did you hear? We started building The Profitable Data Engineer Framework. Join now and let me help you increase your income as an influential data engineer.